BIG DATA ANALYTICS: DIRECTION AND IMPACT ON FINANCIAL TECHNOLOGY
| Autor: | Arun Khatri, NP Singh, Nakul Gupta |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Volume: 8, Issue: 4 218-234 Journal of Management Marketing and Logistics |
| ISSN: | 2148-6670 |
| Popis: | Purpose- Digital infrastructure and technology advancements are steering the innovations in financial sector globally. The technology and datadriven aspect has fueled the Fintech sector, evolving at the tangent of mighty finance sector and revolutionary technology domain, especially thedigital technologies. The purpose of this paper is to show that most FinTech innovations, are significantly driven by big data analytics and itsefficient implementation.Methodology- The use of latest ICT technologies lightens up the finance operations and services to exponential levels. Big data analytics is newand requires comprehensive studies as a research field specially in the finance domain. The intent here is to study an adoption model specially ITdiffusion mode to Big data analytics that could detect key success predictors. The study tests the model for adoption of big data as noveltechnology and the related issues. The paper also presents a review of academic journals, literature, to study the diffusion and adoption of bigdata in to the finance domain.Findings - The research reflects a significant interest and utility about Big data analytics value that epitomizes the rise of Fintech phenomenon.Big data analytics may provide some competencies to the organizations that may consider its several dimensions along with its framework in thepre-adoption phase or adoption phase or implementation or diffusion phase. The research also attempts to describe the several dimensions ofBig data analytics as a new technology. This shall be of good interest to the researchers, professionals, academicians and policy-makers.Conclusion- The paper first defines big data to consolidate the different discourse and literature on big data. We also reflect the point thatpredictive-analytics (with structured data) overshadows other forms: descriptive and prescriptive analytics (with unstructured data) whichconstitutes more than 90% of big data. We also reflected on analytics techniques for unstructured data: audio, video, and social media data, aswell as predictive analytics. In the analysis and testing part we also performed the testing of the IT diffusion model which concludes that thereare significant relationships among IT-planning, IT-implementation and IT-diffusion. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|